Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)

Numerical weather prediction models rely on parameterizations for subgrid-scale processes, e.g., for cloud microphysics, which are a well-known source of uncertainty in weather forecasts. Via algorithmic differentiation, which computes the sensitivities of prognostic variables to changes in model pa...

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Published in:Geoscientific Model Development
Main Authors: Neuhauser, Christoph, Hieronymus, Maicon, Kern, Michael, Rautenhaus, Marc, Oertel, Annika, Westermann, Rüdiger
Format: Text
Language:English
Published: 2023
Subjects:
Online Access:https://doi.org/10.5194/gmd-16-4617-2023
https://gmd.copernicus.org/articles/16/4617/2023/
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spelling ftcopernicus:oai:publications.copernicus.org:gmd109654 2023-09-05T13:21:40+02:00 Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1) Neuhauser, Christoph Hieronymus, Maicon Kern, Michael Rautenhaus, Marc Oertel, Annika Westermann, Rüdiger 2023-08-17 application/pdf https://doi.org/10.5194/gmd-16-4617-2023 https://gmd.copernicus.org/articles/16/4617/2023/ eng eng doi:10.5194/gmd-16-4617-2023 https://gmd.copernicus.org/articles/16/4617/2023/ eISSN: 1991-9603 Text 2023 ftcopernicus https://doi.org/10.5194/gmd-16-4617-2023 2023-08-21T16:24:14Z Numerical weather prediction models rely on parameterizations for subgrid-scale processes, e.g., for cloud microphysics, which are a well-known source of uncertainty in weather forecasts. Via algorithmic differentiation, which computes the sensitivities of prognostic variables to changes in model parameters, these uncertainties can be quantified. In this article, we present visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along strongly ascending trajectories, so-called warm conveyor belt (WCB) trajectories. We propose a visual interface that enables us to (a) compare the values of multiple sensitivities at a single time step on multiple trajectories, (b) assess the spatiotemporal relationships between sensitivities and the trajectories' shapes and locations, and (c) find similarities in the temporal development of sensitivities along multiple trajectories. We demonstrate how our approach enables atmospheric scientists to interactively analyze the uncertainty in the microphysical parameterizations and along the trajectories with respect to the selected prognostic variable. We apply our approach to the analysis of WCB trajectories within extratropical Cyclone Vladiana, which occurred between 22–25 September 2016 over the North Atlantic. Peaks of sensitivities that occur at different times relative to a trajectory's fastest ascent reveal that trajectories with their fastest ascent in the north are more susceptible to rain sedimentation from above than trajectories that ascend further south. In contrast, large sensitivities to cloud condensation nuclei (CCN) activation and cloud droplet collision in the south indicate a local rain droplet formation. These large sensitivities reveal considerable uncertainty in the shape of clouds and subsequent rainfall. Sensitivities to cloud droplets' formation and subsequent conversion to rain droplets are also more pronounced along convective ascending trajectories than for slantwise ascents. The ... Text North Atlantic Copernicus Publications: E-Journals Geoscientific Model Development 16 16 4617 4638
institution Open Polar
collection Copernicus Publications: E-Journals
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language English
description Numerical weather prediction models rely on parameterizations for subgrid-scale processes, e.g., for cloud microphysics, which are a well-known source of uncertainty in weather forecasts. Via algorithmic differentiation, which computes the sensitivities of prognostic variables to changes in model parameters, these uncertainties can be quantified. In this article, we present visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along strongly ascending trajectories, so-called warm conveyor belt (WCB) trajectories. We propose a visual interface that enables us to (a) compare the values of multiple sensitivities at a single time step on multiple trajectories, (b) assess the spatiotemporal relationships between sensitivities and the trajectories' shapes and locations, and (c) find similarities in the temporal development of sensitivities along multiple trajectories. We demonstrate how our approach enables atmospheric scientists to interactively analyze the uncertainty in the microphysical parameterizations and along the trajectories with respect to the selected prognostic variable. We apply our approach to the analysis of WCB trajectories within extratropical Cyclone Vladiana, which occurred between 22–25 September 2016 over the North Atlantic. Peaks of sensitivities that occur at different times relative to a trajectory's fastest ascent reveal that trajectories with their fastest ascent in the north are more susceptible to rain sedimentation from above than trajectories that ascend further south. In contrast, large sensitivities to cloud condensation nuclei (CCN) activation and cloud droplet collision in the south indicate a local rain droplet formation. These large sensitivities reveal considerable uncertainty in the shape of clouds and subsequent rainfall. Sensitivities to cloud droplets' formation and subsequent conversion to rain droplets are also more pronounced along convective ascending trajectories than for slantwise ascents. The ...
format Text
author Neuhauser, Christoph
Hieronymus, Maicon
Kern, Michael
Rautenhaus, Marc
Oertel, Annika
Westermann, Rüdiger
spellingShingle Neuhauser, Christoph
Hieronymus, Maicon
Kern, Michael
Rautenhaus, Marc
Oertel, Annika
Westermann, Rüdiger
Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
author_facet Neuhauser, Christoph
Hieronymus, Maicon
Kern, Michael
Rautenhaus, Marc
Oertel, Annika
Westermann, Rüdiger
author_sort Neuhauser, Christoph
title Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
title_short Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
title_full Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
title_fullStr Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
title_full_unstemmed Visual analysis of model parameter sensitivities along warm conveyor belt trajectories using Met.3D (1.6.0-multivar1)
title_sort visual analysis of model parameter sensitivities along warm conveyor belt trajectories using met.3d (1.6.0-multivar1)
publishDate 2023
url https://doi.org/10.5194/gmd-16-4617-2023
https://gmd.copernicus.org/articles/16/4617/2023/
genre North Atlantic
genre_facet North Atlantic
op_source eISSN: 1991-9603
op_relation doi:10.5194/gmd-16-4617-2023
https://gmd.copernicus.org/articles/16/4617/2023/
op_doi https://doi.org/10.5194/gmd-16-4617-2023
container_title Geoscientific Model Development
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